Improvement of Powertrain Mechatronic Systems for Lean Automotive Manufacturing

Abstract In recent years, the increasing severity of emission standards forced car manufacturers to integrate vehicle powertrains with additional mechatronic elements, consisting in sensors, executors and controlling elements interacting with each other. However, the introduction of the best available ecological devices goes hand in hand with the legislation and/or limitations in different regional markets. Thus, the designers adapt the mechatronic system to the target emission standards of the produced powertrain. The software embedded into the Engine Control Unit (ECU) is highly customized for the specific configurations: variability in mechatronic systems leads to the development of several software versions, lowering the efficiency of the design phase. Therefore the employment of a standard for the communication among sensors, actuators and the ECU would allow the development of a unique software for different configurations; this would be beneficial from a manufacturing point of view, enabling the simplification of the design process. Obviously, the new software must still guarantee the proper level of feedbacks to the ECU to ensure the compliance with different emission standards and the proper engine behavior. The general software is adapted to the powertrain: according to the specific target emission standard, some control elements may not be necessary, and a part of the software may be easily removed. In this paper, starting from a real case-study, a more general methodology is proposed for configurations characterized by different powertrain sets and manufacturing line constraints. The proposed technique allows to maintain the accuracy of the control system and improve process efficiency at the same time, ensuring lean production and lowering manufacturing costs. A set of mathematical techniques to improve software efficacy is also presented: the resulting benefits are enhanced by software standardization, because the design effort may be shared by the largest possible number of applications.